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Showing papers in "Computer Methods and Programs in Biomedicine in 2019"


Journal ArticleDOI
TL;DR: A novel and effective approach was proposed for both ECG signal compression, and their high-performance automatic recognition, with very low computational cost.

233 citations


Journal ArticleDOI
TL;DR: An innovative machine learning methodology is described that enables an accurate detection of CAD and applies it to data collected from Iranian patients and shows that machine-learning techniques optimized by the proposed approach can lead to highly accurate models intended for both clinical and research use.

190 citations


Journal ArticleDOI
TL;DR: The lung segmentation method demonstrates in this work that the problem of dense abnormalities in Chest X-rays can be efficiently addressed by performing a reconstruction step based on a deep convolutional neural network model.

167 citations


Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors developed a machine learning model to predict FLD that could assist physicians in classifying high-risk patients and make a novel diagnosis, prevent and manage FLD.

166 citations


Journal ArticleDOI
TL;DR: The study findings suggest that the machine learning approach had a better performance than the existing sepsis scoring systems in predicting septicaemia.

138 citations


Journal ArticleDOI
TL;DR: The nanomaterial has been used in flow of Ree-Eyring fluid between two rotating disks for thermal conductivity enhancement of base fluid and entropy rate and Bejan number show the dual behaviors against Eckert number.

131 citations


Journal ArticleDOI
TL;DR: This study found that of the six medical tasks that exist, the diagnosis medical task was that most frequently researched, and that the experiment-based empirical type and evaluation-based research type were the most dominant approaches adopted in the selected studies.

128 citations


Journal ArticleDOI
TL;DR: The presented approach outperformed as compared to existing approaches in segmentation and specificity, sensitivity, accuracy, area under the curve (AUC) and dice similarity coefficient (DSC) at the fused feature based level.

125 citations


Journal ArticleDOI
TL;DR: The proposed Separable-Unet framework takes advantage of the separable convolutional block and U-Net architectures to enhance the pixel-level discriminative representation capability of fully Convolutional networks (FCN).

107 citations


Journal ArticleDOI
TL;DR: This article provides a comprehensive review of automated sleep stage scoring systems, which were created since the year 2000, and shows that all of these signals contain information forSleep stage scoring.

99 citations


Journal ArticleDOI
TL;DR: Both models successfully explain the enhancement of heat transfer character of nanofluids by analysing the obtained exact Nusselt numbers involving several parameters of physical interest.

Journal ArticleDOI
TL;DR: Mixed convective flow hybrid nanomaterial over a convectively heated surface of disk shows that velocity of liquid particles decline against magnetic parameter and temperature, and Magnitude of surface drag force increases for higher values of stretching and magnetic variables.

Journal ArticleDOI
TL;DR: The designed deep learning approaches performed better than those developed and tested in previous studies in terms of detecting SA events, and they could distinguish between apnea and hypopnea events using an ECG signal.

Journal ArticleDOI
TL;DR: The machine learning-based approach applied in this study is able to predict, with a high accuracy, the outbreak of cardiovascular diseases in patients on dialysis.

Journal ArticleDOI
TL;DR: XGBoost was improved and firstly introduced in single heartbeat classification as both high positive predictive value for N class and high sensitivities for abnormal classes were provided and a comparison showed the effectiveness of the novel method.

Journal ArticleDOI
TL;DR: A classification scheme involving a convolutional neural network trained to discriminate among eight classes of cells circulating in peripheral blood cells with high accuracy by means of a transfer learning approach using convolutionAL neural networks is proposed.

Journal ArticleDOI
TL;DR: Evaluate Cutpoints allows not only dichotomization of populations into groups according to continuous variables and binary variables, but also stratification into three groups as well as manual selection of cutoff point thus preventing potential loss of information.

Journal ArticleDOI
TL;DR: The analysis shows that the proposed classifier has comparatively improved performance and determines the leukemia from the blood smear images and is compared with the state of the art methods.

Journal ArticleDOI
TL;DR: The proposed method provides better emotion recognition performance as compared to the state-of-the-art methods and classifies emotions using single-bipolar EEG channel, which can greatly reduce the complexity of emotion-recognition based BCI systems.

Journal ArticleDOI
TL;DR: Results from real patient fracture data sets demonstrate the feasibility using deep CNN and SURF for computer-aided classification and detection of the location of calcaneus fractures in CT images.

Journal ArticleDOI
TL;DR: A wide and deep learning model is applied that combines the strength of a generalised linear model with various features and a deep feed-forward neural network to improve the prediction of the onset of type 2 diabetes mellitus (T2DM).

Journal ArticleDOI
TL;DR: RF-based model with statistical tests for detection of high risk genes showed the best performance for accurate cancer classification in multi-center clinical trials.

Journal ArticleDOI
TL;DR: In this article, the authors evaluated the performance of deep learning-based systems to automatically map clinical notes to ICD-9 medical codes using the Medical Information Mart for Intensive Care (MIMIC-III) dataset.

Journal ArticleDOI
TL;DR: The method developed by the authors to address the border of the lesion detection in dermoscopy images is proven to be robust and reliable and could also be used to deal with other segmentation problems of a similar nature.

Journal ArticleDOI
TL;DR: The proposed layered structure identifies all the three classes of skin diseases with a highly acceptable classification accuracy of 98.99%, 97.54% and 99.65% for melanoma, dysplastic nevi and BCC respectively.

Journal ArticleDOI
TL;DR: The novelty of the study is the use of a data mining approach on the spatial and temporal parameters of gait analysis in order to classify patients affected by typical (PD) and atypical Parkinsonism (PSP) based on gait patterns.

Journal ArticleDOI
TL;DR: This work develops the compound.Cox R package that implements univariate significance tests (via the Wald tests or score tests) for feature selection and provides three algorithms for constructing a multigene predictor, which are tailored to the subset of genes obtained from univariate feature selection.

Journal ArticleDOI
TL;DR: The proposed novel adaptive color deconvolution (ACD) algorithm can be efficiently solved and is effective to improve the performance of cancer image recognition, which is adequate for developing automatic CAD programs and systems based on WSIs.

Journal ArticleDOI
TL;DR: The theoretical analysis presented under long wavelength approximation serves as a model for the creeping non-isothermal flow of blood through a diseased segment of the artery due to vasomotion (peristaltic motion) in the artery.

Journal ArticleDOI
TL;DR: A novel method fusing energy entropy and morphological features for MI detection via 12 leads ECG that has the characteristic of interpretability according with diagnostic logic and strategy of clinician and specific change of ECG for MI.